Methods and apparatus to identify publisher advertising behavior

ABSTRACT

Methods, apparatus, systems and articles of manufacture are disclosed to identify publisher advertising behavior. An example disclosed method includes initiating a first probing effort of an Internet publisher of interest to establish a baseline advertising ratio for a plurality of advertisers, determining a first advertising deviation based on a difference between the baseline advertising and a local advertising associated with a first geography of interest, and establishing a first probing frequency for the first geography of interest based on the first advertising deviation.

RELATED APPLICATION

This patent is a continuation of, claims the benefit of and priority topreviously filed U.S. patent application Ser. No. 14/529,315, entitled“METHODS AND APPARATUS TO IDENTIFY PUBLISHER ADVERTISING BEHAVIOR,”filed Oct. 31, 2014. The subject matter of this application isincorporated herein by reference in its entirety.

FIELD OF THE DISCLOSURE

This disclosure relates generally to market research, and, moreparticularly, to methods and apparatus to identify publisher advertisingbehavior.

BACKGROUND

Media research efforts include identifying instances of mediapresentation via various media delivery systems. In some cases,broadcast television broadcasts are monitored to identify whichcommercials and/or programs are presented at corresponding times of day.In other cases, radio broadcasts are monitored to identify one or moreradio advertisements presented at corresponding times of day. Thecollected media information may be further analyzed to identify one ormore aspects of advertising behavior.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 are example tables illustrating baseline advertising ratios forInternet publishers.

FIG. 2 are example tables illustrating general skew of the exampleInternet publishers of FIG. 1 to identify a quantity of advertisingratio deviation in geographies of interest.

FIG. 3 is an example table illustrating special skew associated with oneof the Internet publishers of FIGS. 1 and 2 .

FIG. 4 is a schematic illustration of an example market evaluationsystem to identify publisher advertising behavior.

FIG. 5 is a schematic illustration of an example implementation of theprobe manager of FIG. 4 to identify publisher advertising behavior.

FIGS. 6 and 7 are flowcharts representative of example machine readableinstructions that may be executed to implement the example marketevaluation system and/or the example probe manager of FIGS. 4 and 5 .

FIG. 8 is a schematic illustration of an example processor platformstructured to execute the instructions of FIGS. 6-7 to implement theexample market evaluation system and/or probe manager of FIGS. 4 and 5 .

DETAILED DESCRIPTION

Market researchers seek to understand local markets in many differentways. In some examples, market researchers study and/or collectinformation associated with audience behaviors, and/or demographics ofthe audience member. In other examples, market researchers study and/orcollect information associated with products and/or services ofadvertisers, merchants, retailers, wholesalers and/or other commercialentities. The information associated with the merchants, retailers,wholesalers, other commercial entities products and/or services offeredto consumers is generally identified through advertising behavior.

Internet-based advertising allows particular advertisements to bepresented on web pages that are sourced by Internet publishers. ExampleInternet publishers include, but are not limited to business newspublishers (e.g., CNN, FOX, HLN, Bloomberg), sports publishers (e.g.,ESPN), entertainment news publishers (e.g., E! Online) and/or weathernews publishers (e.g., The Weather Channel). In some examples, theInternet publisher will reserve one or more portions of its web page(s)to host advertisements that are available for purchase. These portionsof web pages reserved for advertising purposes are referred to herein as“ad space.” The ad space may be purchased by the aforementionedadvertising merchants, retailers, wholesalers, and/or other commercialentities (e.g., manufactures/suppliers of products and/or services) sothat visitors to the web page(s) are exposed to correspondingadvertisements.

In some examples, the Internet publisher's web page presents the sameadvertisement(s) in the purchased ad space regardless of the geographyin which the web page is rendered. For example, a cola manufacturer(e.g., Coke) may purchase ad space from a national news publisher (e.g.,CNN) such that a viewer sees the cola advertisement when the web page isaccessed from a web page browsing device (e.g., a computing device(e.g., a personal computer, a wireless telephone, a tablet, etc.) with aweb browser) irrespective of the browser physical location (e.g., thesame advertisement is displayed by browsers in California, Washington,Maine and Florida). In other words, the advertisement presented in thead space for the national news publisher does not change based on thegeographic location of the rendered web page within the correspondingnation (e.g., the United States).

In some examples, the Internet publisher's web page presents differentadvertisement(s) in the purchased ad space based on the geographiclocation of the browser rendering the advertisement. For example, alocal sports team in California (e.g., The San Francisco 49ers) maypurchase ad space from a sports news publisher (e.g., ESPN) such that aviewer in California sees advertisements for 49ers merchandise and gametimes. However, a local sports team in Florida (e.g., The JacksonvilleJaguars) may also purchase ad space from the same sports news publisher(e.g., ESPN) such that a viewer in Florida sees advertisements forJaguars merchandise and game times. In other words, the advertisementsassociated with the sports news publisher are relatively dependent onthe geographic location of the rendered web page.

Ad space allocated by Internet publishers is typically managed by one ormore third party advertising networks (ad networks), such as GoogleDouble-Click. The ad networks sell ad space to purchasers (e.g.,manufacturers of products/services, syndicated television producers,movie producers, theater companies, etc.) and then the ad networks placethe desired advertisements in the ad space without further involvementby the Internet publisher(s). In other words, the Internet publishersallow the ad networks to market the ad space for a fee. In someexamples, Internet publishers may manage their own ad space and workdirectly with one or more purchasers. In either case, market researchersdesire information related to which advertisements occur with particularInternet publishers, and whether such advertisements are placed as afunction of geography. For example, market researchers desireinformation related to whether the advertisements occur in a homogeneousmanner, a non-homogeneous manner, or any intermediate degree thereofbased on one or more geographies of interest. Internet publishers thatexhibit a relatively homogeneous presentation of advertisements (e.g.,little or no variance across different geographies) are considered tohave a relatively lower degree of skew when compared to Internetpublishers that exhibit a relatively non-homogeneous presentation ofadvertisements (e.g., different advertisements in differentgeographies).

To identify whether an Internet publisher exhibits a particular degreeof skew, market researchers initiate web page probes that originate ingeographies of interest. For example, the market researcher may own,manage and/or otherwise control one or more web page browsing devices ina first geography of interest and a second geography of interest. Theone or more web page browsing devices may be implemented as a serverfarm within the geography of interest having any number of computerswith Internet browsers that are instructed to initiate web page requestson a periodic, aperiodic, scheduled and/or manual basis. When a web pagerequest for a particular Internet publisher of interest (e.g., ESPN vianavigation to www.espn.com) is initiated (e.g., a probe) within thefirst geography of interest (e.g., California), a first advertisement(e.g., an advertisement for the 49ers) may appear within the ad space ofthe Internet publisher. However, when another web page request for thesame Internet publisher of interest is initiated (e.g., a probe) withinthe second geography of interest (e.g., Florida), a second advertisement(e.g., an advertisement associated with the Jaguars) may appear withinthe same ad space of the Internet publisher. While the example describedabove refers to a first advertisement and a second advertisement,examples disclosed herein account for an aggregate number of instancessuitable for statistical significance.

In the illustrated example above, a relatively high degree of skew isobserved and expected due to the localized sports culture differencesbetween the first and second geographies of interest. However, in someexamples an Internet publisher may exhibit different degrees of skewbased on any number of factors. For example, a national news publisher(e.g., CNN) may generally exhibit a relatively low amount of skew, inwhich the same advertisements are placed in the ad space when the webpage is accessed from the first geography of interest or the secondgeography of interest. As used herein, “general skew” is a measure ofthe degree of non-homogeneous advertising activity for the publisher inparticular geographies, and reflects a nominal or steady state value ofadvertising activity. For instance, the ad space of the national newspublisher may have been purchased by a cola manufacturer that wishes toplace advertising in both example geographies of interest. On the otherhand, and as used herein, a “baseline ad ratio” reflects a proportionateamount of advertising for each advertiser that purchases ad space fromthe Internet publisher independent of particular geographies ofinterest.

One or more localized factors may cause skew to increase. Assume, forexample, advertisements in the first geographic area of interest differfrom the advertisements in the second geographic area of interest. Now,assuming for purposes of illustration that, during a presidentialelection, the first geography of interest is not a particularlyimportant battleground state for one of the presidential candidates and,thus, the example advertisements from the cola manufacturer continue inthe first geographic area without change. However, assume, in thisexample, that the second geography of interest is a key battlegroundstate for one of the presidential candidates, and that an amount ofadvertising associated with that candidate occurs and replaces a portionof the advertisements that would otherwise be purchased by the colamanufacturer. As used herein, “special skew” is a metric related to athreshold amount of deviation in advertising behavior from the baselinead ratio value(s). In some examples, special skew may be identifiedbased on a threshold amount of ad ratio deviation in a geography ofinterest at one moment in time as compared to a separate moment in time.

Internet publishers that do not exhibit a relatively high degree of skew(e.g., a threshold percentage value) may not require web page probingefforts to occur as frequently when compared to Internet publishers thatexhibit a lower degree of skew. As described above, computing resourcesresiding in different geographic locations of interest are used tofacilitate one or more probes of the web page. For example, in the eventa sample of ad space behavior was desired from each state in the UnitedStates, then fifty (50) separate server farms may be allocated to theUnited States in which one server farm is placed in each of the 50states. While the example above refers to a resolution at a state level,examples disclosed herein are not limited thereto. Geographicresolutions of interest may be analyzed at any level, such as a citylevel within a state of interest, a regional level representing severalstates of interest, a country level, etc. For instance, a server farm inJacksonville, Fla., a server farm in St. Augustine, Fla., a server farmin Gainesville, Fla. etc, can be used to study markets dispersedthroughout Florida. In some examples, the market researcher investscapital in the form of computer equipment to initiate the probes, rentaland/or building costs to house the computer equipment, and/or personnelcosts to maintain the computer equipment in proper working order. Insome examples, the market researcher employs proxy services having aper-probe fee rather than expend the capital necessary to facilitateprobes in one or more desired geographies of interest. One example proxyservice is GeoSurf™, which owns and operates proxy locations throughoutthe world, and offers access to such proxy locations for a fee. Ineither case, as the number of requested probes increases, so does thecost of probing efforts.

Example methods, apparatus, systems and/or articles of manufacturedisclosed herein identify skew values for Internet publishers so that aprobing rate may be established in proportion to the advertisingdiversity of the Internet publisher and/or the advertising diversity ofthe Internet publisher for a particular geographic region of interest.FIG. 1 are example tables illustrating baseline advertising ratios (adratios) 100 for a first Internet publisher and a second Internetpublisher of interest. As described in the example above, the baselinead ratio reflects a proportionate amount of advertising for each of twoadvertisers that purchases ad space for the Internet publisher. Thus,the baseline ad ratio reflects all advertising purchased by the twoadvertisers as a percentage metric that is independent of geography, andis sometimes referred to as total advertising.

In the illustrated example of FIG. 1 , a first Internet publisherbaseline table 102 is associated with cnn.com and includes an advertisercolumn 104 and an ad ratio column 106. Because the first Internetpublisher baseline table 102 reflects all advertising for cnn.com, thecorresponding ad ratio values for each of the advertisers accumulate to100%. A second Internet publisher baseline table 110 in the illustratedexample of FIG. 1 is for espn.com and includes an advertiser column 112and an ad ratio column 114. As described above, because the secondInternet publisher baseline table 110 reflects all advertising forespn.com, the corresponding ad ratio values for each of the advertisersaccumulate to 100%. While the illustrated example of FIG. 1 includes afirst Internet publisher baseline table 102 and a second Internetpublisher baseline table 110, examples disclosed herein may include anynumber of Internet publisher baseline tables.

In some examples, each Internet publisher baseline table of interest maybe established and/or otherwise determined in response to proxy probingefforts in geographies of interest for an analysis period of interest.For example, probing of the website cnn.com from proxies at eachgeography of interest may be initiated for a 24-hour period to capture alist of all advertisers that utilize ad space from cnn.com.Additionally, probing of the website espn.com from the same proxies ateach geography of interest may be initiated for a 24-hour period tocapture a list of all advertisers that utilize ad space from espn.com.During the example time period of probing (e.g., 24-hour period, 2-dayperiod, 1-week period, etc.), the proxies may be instructed to perform aprobe once every minute, once every five-minutes, or at any otherprobing frequency desired to capture the baseline ad ratios for each ofthe Internet publishers of interest.

However, while initial probing efforts are applied to establish thebaseline ad ratios and establish a thorough list of advertisers,subsequent probing efforts may be adjusted to occur at an alternate(e.g., lower) frequency depending on advertising diversity occurringwith respect to one or more particular geographies of interest. Asdescribed above, probing efforts include an associated cost per probe.Example methods, apparatus, systems and/or articles of manufacturedisclosed herein allow determination of a probing frequency which isproportionate to a corresponding advertising diversity for respectivegeographies of interest, thereby saving expenditures of computingresources, reducing network bandwidth usage, and/or reducing costs formarket research efforts. In some examples, probing efforts may bethwarted by one or more websites that track probing frequencies. Forinstance, in the event a website notices a threshold number of probes toits website, then one or more blocking efforts may be established bythat website to prevent further probing efforts to operate. In otherwords, an Internet protocol (IP) address associated with a request tothe website may be blocked, thereby preventing the request fromreturning and/or otherwise rendering the content of the probed website.In some examples, the website may interpret relatively heavy probingefforts as excessive bot behavior (e.g., robots rather than humanactivity), and identify the corresponding IP address and/or user agentinformation for blocking purposes.

FIG. 2 are two example general skew tables 200 to indicate how thesedifferent geographies of interest differ from the example baselineratios of FIG. 1 . In the illustrated example of FIG. 2 , a firstgeneral skew table 202 is associated with the Internet publisher cnn.comand includes an advertiser column 204 and an ad ratio deviation column206. The advertisers listed in the example advertiser column 204 are thesame advertisers that were involved in the baseline ad ratio probingeffort, as shown in column 104 of FIG. 1 . The ad ratio deviation valuesin the example ad ratio deviation column 206 correspond to respectiveones of the geographies of interest for the corresponding advertisement.While the illustrated example of FIG. 2 includes three examplegeographies of interest (i.e., New York (N.Y.), Florida (FL) and Alabama(AL)), any number of geographies and/or regions of interest may beapplied in the examples disclosed herein. The illustrated example ofFIG. 2 also includes a second general skew table 210 associated with theInternet publisher espn.com and includes an advertiser column 212 and anad ratio deviation column 214. The two tables 202, 210 of FIG. 2 aresimilar in format, but reference different Internet publishers. Thus,the above discussion of the first table 202 applies analogously to thesecond table 210.

In the illustrated example of FIG. 2 , the ad ratio deviations reflectan amount (e.g., a percentage) of change in advertising presence for therespective geography of interest when compared with the correspondingbaseline ad ratio of FIG. 1 , in which the baseline ad ratio issometimes referred to herein as the general skew. For example, an adratio deviation for cnn.com for the advertiser Coke is 1% higher in NewYork (220) than for the baseline ad ratio (see FIG. 1 , where the Cokebaseline ad ratio is 13%), but an ad ratio deviation for cnn.com for thesame advertiser is 2% lower in Alabama (222). In another example, an adratio deviation for espn.com for the advertiser Coke is 20% lower in NewYork (224) than for the baseline ad ratio (see FIG. 1 , where the Cokebaseline ad ratio is 24% for espn.com). An ad ratio deviation forespn.com for the same advertiser (Coke) is 30% higher in Alabama (226).

The general skew provides an indication of how much advertisingdiversity occurs for each Internet publisher of interest with respect toa particular advertiser in a particular geography. For instance, theadvertiser Coke exhibits relatively low ad ratio deviation values fromdifferent geographies when advertising with the Internet publishercnn.com when compared with advertising with the Internet publisherespn.com. In other words, the relative magnitudes of the ad ratiodeviations for Coke between New York, Florida and Alabama differ bythree percentage points when advertising with cnn.com (AL=−2%, NY=+1%,FL=+1%), but the relative magnitudes of the ad ratio deviations for Cokebetween those same geographies differ by fifty percentage points whenadvertising with espn.com (AL=+30%, NY=−20%, FL=+14%). Such differencesin standard deviation reflect a relatively greater degree of advertisingdiversity between geographies of interest for espn.com than for cnn.com.

Based on the advertising diversity identified for the Internet publishercnn.com, a proportional probing frequency is established for cnn.com.Merely causing proxy resources to conduct probing at a default probingfrequency for all Internet publishers of interest would cause a waste ofresources (e.g., extra bandwidth usage, extra inventory storage usage,extra processor cycle usage, etc.) for some Internet publishers having arelatively low advertising diversity if such default probing frequencyis set too high. Conversely, if the default probing frequency were settoo low, it would cause an insufficient analysis of Internet publishershaving a relatively higher advertising diversity. To overcome theseproblems, example methods, apparatus, systems and/or articles ofmanufacture disclosed herein establish and/or otherwise determine aprobing frequency of a given Internet publisher based on observedadvertising diversity behavior of that particular Internet publisher.Moreover, such probing frequency may be set to different values ingeographies of interest based on the observed advertising diversitybehavior.

As described above, an Internet publisher that exhibits a relatively lowamount of advertising diversity (skew) may, for various reasons, exhibitgreater amounts of skew at a different time. In such examplecircumstances, a corresponding probing frequency may need to change toadequately capture the advertising behavior of the Internet publisher ofinterest. FIG. 3 is an example subsequent skew table 300 calculated at asubsequent time from when the first general skew table 202 of FIG. 2 wascalculated for the Internet publisher cnn.com. In the illustratedexample of FIG. 3 , the subsequent skew table 300 includes an advertisercolumn 302 and an ad ratio deviation column 304 similar to the tableformat shown in FIG. 2 . The example subsequent skew table 300 revealsthat ad ratio deviation values for the example geographies of New Yorkand Alabama do not differ substantially from the baseline ad ratiosidentified in the illustrated example of FIG. 1 . In particular, theexample ad ratio deviation values for the example geographies of NewYork and Alabama are the same as those identified in the previousanalysis shown in FIG. 2 , and only deviate from the baseline ad ratiosby −9% at the lowest, and by +6% at the highest. In some examples, thedeviation of ad ratio values from different geographies of interest maybe identified based on a standard deviation value therebetween.

In the illustrated example of FIG. 3 , the Florida geography nowexhibits an ad ratio deviation (306) having a higher value than what waspreviously observed in the illustrated example of FIG. 2 . Inparticular, for the Internet publisher cnn.com, the ad ratio deviationassociated with Coke advertisements are 21% lower than the baseline adratio of 13%, which is a change of twenty-two percentage points (22%)when compared to the general skew calculation (250) of FIG. 2 . In someexamples, special skew may be identified and/or otherwise categorizedbased on a threshold deviation value from a previous skew calculation.In still other examples, special skew may be identified and/or otherwisecategorized based on a threshold standard deviation from the baseline adratio value(s) (see FIG. 1 ). In some examples, sourcing effects may beidentified by comparing directional magnitudes of ad ratio deviationvalues from two or more geographies of interest. For instance, the adratio deviation in the example subsequent skew table 300 of FIG. 3associated with AARP advertisements 308 in Florida 310 is +210%, and thead ratio deviation in that same geography of interest (i.e., Florida)for all other advertisers is negative (i.e., Coke=−21%, Pepsi=−34%, AXEBody Spray=−26%, Chevy=−11%, BMW=−18%, McDonalds=−14% and Walmart=−27%).In other words, the advertiser AARP focused a relatively substantialadvertising effort in Florida that would have otherwise been availableto other advertisers, thereby essentially depriving the otheradvertisers from the opportunity of advertising with cnn.com.

In the illustrated example of FIG. 3 , one or more ad ratio deviationthreshold values may be identified to reveal an occurrence of specialskew. For example, in the event an ad ratio deviation magnitude inexcess of 50% is identified, then the geography of interest may beconsidered to exhibit special skew behavior. Using an example ad ratiodeviation threshold of 50%, the example geography of Florida 310 isidentified as exhibiting special skew because its corresponding ad ratiodeviation value is +200% (i.e., greater than the threshold of 50%).After one or more instances of special skew is identified, examplemethods, apparatus, systems and/or articles of manufacture disclosedherein respond by modifying and/or otherwise re-evaluating probingfrequency efforts associated with the affected geography of interest. Asdescribed above, probing efforts may be adjusted to reduce (e.g.,minimize) wasted probing efforts for geographic regions of interest thatdo not exhibit at least a particular value of ad ratio deviation (e.g.,expressed as a percentage value). When probing instances occur for aparticular geography of interest that does not exhibit a sufficient adratio deviation, then computing resources (e.g., processor cycles,bandwidth usage, etc.) are wasted on such probing efforts that couldotherwise be directed to other uses (e.g., one or more alternategeographies of interest that exhibit relatively greater amounts of adratio deviation).

FIG. 4 is a schematic illustration of an example market evaluationenvironment 400. In the case of FIG. 4 , the United States of America isidentified as an analysis geography 402. In the illustrated example ofFIG. 4 , the analysis geography 402 includes any number of geographiesof interest, such as one or more region(s) of interest (e.g., Southeast,Northeast, Pacific Northwest, etc.), one or more state(s) of interest(e.g., New York, Florida, Alabama), one or more counties of interest,and/or one or more cities of interest. In response to an Internet probe,an Internet browser located in a geography of interest sends an HTTPrequest to a web address of interest (e.g., a uniform resource locator(URL)) for an Internet publisher of interest (e.g., CNN viahttp://cnn.com, ESPN via www.espn.com, etc.). Publisher advertisingbehavior may occur via any appropriate type of distribution systemand/or network and may use any type of media such as audio, still image,moving image and/or combinations thereof presented and/or capable ofbeing presented to an audience. In some examples, Internet media thatoccupies ad space purchased by an advertiser includes a still imagebanner advertisement having text and/or images, moving images (e.g.,portions of movies, television shows, newscasts, etc.) and/or imagesaccompanied by audio. The publisher advertising behavior is captured toallow market research analysis, such as identifying particularadvertisers, identifying particular advertisement media types,identifying variation in which advertisers occupy the purchased ad spaceat which periods of time (e.g., coffee advertiser activity duringmorning hours, television broadcaster advertiser activity during lateafternoon hours, etc.).

As described above, the example Internet browser located in thegeography of interest may be executed on a computing device (e.g., aserver, a personal computer, a server farm, etc.) that is physicallylocated in or near the geography of interest. In the illustrated exampleof FIG. 4 , the computing devices are implemented by proxy servers. Inthis example, three proxy servers are shown; an Atlanta proxy server404, an Orlando proxy server 406 and a New York proxy server 408. AnInternet probe performed by the example Atlanta proxy server 404 resultsin the Internet browser (e.g., an Internet browser executed by theAtlanta proxy server 404) navigating to the Internet publisher ofinterest (e.g., CNN via http://cnn.com) and capturing data (e.g., screenshots, optical character recognition, etc.) associated with ad spacepresented on the Internet publisher of interest at that time. Generallyspeaking, each geography of interest may exhibit ad space usageassociated with global/national brands (e.g., nationally recognizedfinancial institutions, airlines, soft drinks, etc.) and/or regional orlocal brands that are marketed in a relatively smaller geography (e.g.,regionally known grocery store chains, local car dealerships, localrestaurants, etc.). On the other hand, an Internet probe performed bythe example Orlando proxy server 406 results in the Internet browsernavigating to the same publisher of interest and capturing dataassociated with ad space presented via that same Internet publisher ofinterest and/or a supporting ad server. Although the same Internetpublisher of interest (e.g., CNN via http://cnn.com) may be probed fromboth the example Atlanta proxy server 404 and the example Orlando proxyserver 406, different advertisements (e.g., representing differentbrands and/or advertisements) may be presented in the associated adspace as seen by the Atlanta server 404 as compared to the advertisingseen by the Orlando server 406. For example, the ad space of theInternet publisher in the state of Florida may include advertisementsassociated with the Jacksonville Jaguars, while the ad space of thatsame Internet publisher in the state of Georgia may includeadvertisements associated with the Atlanta Falcons. Of course, ad spacefor any particular Internet publisher may be utilized by any type ofadvertiser that secures rights to the ad space based on, for example,bidding a relative highest amount of money for the ad space. As such, anadvertiser associated with a branded beverage (e.g., Coke®) may outbidan advertiser in Georgia associated with the Atlanta Falcons.

While three example proxy servers are shown in the illustrated exampleof FIG. 4 , such examples are for illustrative purposes and notlimitation. Any number of proxy servers may be considered and/orotherwise operate in a market evaluation environment, such as theillustrated market evaluation environment 400 of FIG. 4 . In someexamples, the proxy servers are owned and operated by the marketresearcher, which requires investment costs for proxy servers (e.g.,computing devices), costs for housing the proxy servers (e.g., leaseproperty, rent property, electrical power costs, thermal management,etc.) and/or costs to maintain the proxy servers (e.g., InformationTechnology personnel). In some examples, the proxy servers are not ownedand operated by the market researcher, but are instead invoked on aper-probe fee structure facilitated by a third party (e.g., GeoSurf™).In either case, conducting one or more probes of Internet publishers ofinterest includes one or more associated financial costs and multiplecosts in terms of computing resources (e.g., bandwidth, processorcycles, and/or memory).

The example Atlanta proxy server 404, the example Orlando proxy server406, the example New York proxy server 408 and/or any other proxyservers that may operate in the example market evaluation environment400 are communicatively connected to the Internet, symbolicallyrepresented as a network cloud 410 in FIG. 4 . In the example of FIG. 4, a publisher evaluator 412 is communicatively connected to the examplenetwork 410 to cause computing resources (e.g., the proxy server(s) 404,406, 408) to identify publisher advertising behavior. After probing oneor more Internet publishers of interest, the probing computing resourcereturns the advertising data and is given to the example publisherevaluator 412. The example publisher evaluator 412 stores acquiredadvertising data associated with ad space content in a memory (e.g., amarket database 420). To establish and/or modify probing rates for oneor more geographies of interest, an example probe manager 414 is invokedby the example publisher evaluator 412.

FIG. 5 is a schematic illustration of an example implementation of theexample probe manager 414 of FIG. 4 . The example probe manager 414identifies publisher advertising behavior and regulates Internetpublisher probing rates by the different probing resources distributedat the geography of interest. In the illustrated example of FIG. 5 , theprobe manager 414 includes a baseline engine 502, a skew engine 504, aprobe interface 506, a publisher manager 508, a geography manager 510,an ad ratio data store 512, a publisher data store 514, a geography datastore 516, and a control bus 518 to facilitate communication within theexample probe manager 414. In operation, the example baseline engine 502determines whether baseline ad ratio values have been acquired and/orotherwise calculated for each Internet publisher of interest, asdescribed above in view of the example tables of baseline ad ratios 100of FIG. 1 . In the event baseline ad ratio values have not been acquiredand/or otherwise calculated for each Internet publisher of interest(e.g., a new provider is added, a new geography of interest is added, anew website for a new or existing publisher is added, etc.), the exampleprobe interface 506 initiates probes to establish a baseline ad ratiovalue for each Internet publisher of interest in each geography ofinterest.

In some examples, the publisher manager 508 maintains a list of Internetpublishers of interest to the market researcher and providescorresponding web address information to the example probe interface 506to be used during one or more probing instances. Additionally, theexample geography manager 510 maintains a list of geographies ofinterest to the market researcher and provides geography information tothe example probe interface 506 so that the geographically specificprobing server can be identified when navigating to the web addressassociated with the Internet publisher of interest. For example, in theevent the Internet publisher “CNN” is to be probed in and/or near thestate of Georgia, then the publisher manager 508 forwards the webaddress http://cnn.com to the example probe interface 506 and theexample geography manager 510 associates the web address http://cnn.comwith the example Atlanta proxy server 404 to identify which computingequipment is to conduct the probe. The probe interface 506 then sends aprobing instruction to the geographic probing devices (e.g., the Atlantaserver). As described above in connection with FIG. 1 , the baseline adratio values (106, 114) are agnostic to geography and, instead, reflectan aggregate consumption of ad space per advertiser for all geographiesof interest.

While the baseline ad ratio values indicate a relative quantity ofadvertising presence for each advertiser of interest on each particularInternet publisher of interest in each geography of interest, a generalskew ad ratio calculated by the example skew engine 504 indicates anamount of deviation from the baseline values on a per-geography basis,as described above in connection with FIG. 2 . In some examples, aparticular geography of interest exhibits, for a particular Internetpublisher, a relatively greater or lesser advertising focus for a brandwhen compared to the baseline ad ratio values. For instance, asdescribed above in connection with FIG. 2 , the example brand Cokeexhibits, for the Internet publisher CNN, an ad ratio deviation of +1%in New York, but exhibits an ad ratio deviation of −2% in Alabama. Inother words, Coke advertisements are run in the geography of New York ata rate slightly greater than the baseline focus, while Cokeadvertisements are run in the geography of Alabama at a rate slightlyless than the baseline focus. As a result, a corresponding probing ratemay be respectively established by the example probe interface 506 basedon a particular magnitude ad ratio deviation for each geography ofinterest. For instance, a separate Internet publisher of interest, suchas ESPN, exhibits ad ratio deviation values for the same brand Coke inthe geographies of New York and Alabama (i.e., New York=−20% andAlabama=+30%). Generally speaking, the ad ratio deviation value of −20%in New York reflects a much lower interest and/or advertising focus ofthe Coke brand for visitors of the ESPN web site, while the ad ratiodeviation value of +30% in Alabama reflects a much higher interestand/or advertising focus of the Coke brand for visitors of the ESPN website.

To illustrate an example manner of establishing a respective probingrate for (a) an Internet publisher of interest within (b) a geography ofinterest, assume that a first probing rate of ten probes per hour is tooccur for a first threshold of ad ratio deviation values, and a secondprobing rate of twenty probes per hour is to occur for a secondthreshold of ad ratio deviation values. Also assume that the firstthreshold of ad ratio deviation values is satisfied within a range of 10percentage points, and the second threshold of ad ratio deviation valuesis satisfied within a range of 20 percentage points. Using the examplegeneral skew values for the Internet publisher CNN from FIG. 2 , theexample skew engine 504 determines that all of the ad ratio deviationvalues have a magnitude of nine (9) percentage points or lower, therebycausing the example probe interface 506 to establish the first probingrate of ten probes per hour for every geography of interest for CNN. Inother words, because the general skew is relatively low, a correspondingprobing rate may be set to a lower value and/or otherwise select probingresources that are relatively less expensive (e.g., probing resourcesmanaged by a market research entity versus probing resources thatoperate on a pay-per-probe basis). On the other hand, using the examplegeneral skew values for the Internet publisher ESPN from FIG. 2 , theexample skew engine 504 determines that every geography of interest hasat least one occurrence of an ad ratio deviation value that is greaterthan 20 percentage points, thereby causing the example probe interface506 to establish a second probing rate (different from the first probingrate) for those geographies of interest for ESPN.com. In other words,because the Internet publisher ESPN exhibits a relatively greater degreeof ad ratio deviation than exhibited by CNN, a corresponding higherprobing rate for ESPN is justified in an effort to accurately capturethe advertising behavior of ESPN's ad space. On the other hand, becauseCNN does not exhibit a relatively high ad ratio deviation, computingresources associated with probing efforts of CNN can be saved (e.g.,repurposed) by establishing a relatively lower probing rate.

While the illustrated example above reflects the Internet publisher CNNas having a relatively low ad ratio deviation, thereby justifying therelatively lower first probing rate, the ad ratio deviation may changeat a later time. For example, one of the advertisers may decide toinject a substantially large amount of advertising dollars in aparticular geography of interest. In some examples, ad space is brokeredvia one or more bidding processes to allow an advertiser with thehighest bid to occupy and/or otherwise populate the ad space of theInternet publisher. In such example cases, the highest biddingadvertiser may increase their advertising presence in that geography ofinterest at the expense of other advertisers that submitted lowerbidding values. In other words, relatively higher bidding advertiserssource advertising presence from the relatively lower biddingadvertisers.

The example skew engine 504 may repeat one or more skew calculations ona periodic, aperiodic, scheduled and/or manual basis to determinewhether special skew conditions are present. As described above, specialskew may be identified by identifying a threshold amount of deviation(e.g., a percentage value) in advertising behavior from the baseline adratio value(s). In the event the skew calculation by the example skewengine 504 results in ad ratio deviation values exceeding the thresholdvalue, the example probe interface 506 may adjust the probing frequencyof the probing computing resources for the affected geographies ofinterest that exhibited more than the threshold change.

While an example manner of implementing the probe manager 414 of FIG. 5is illustrated in FIGS. 1-4 , one or more of the elements, processesand/or devices illustrated in FIGS. 4 and 5 may be combined, divided,re-arranged, omitted, eliminated and/or implemented in any other way.Further, the example baseline engine 502, the example skew engine 504,the example probe interface 506, the example publisher manager 508, theexample geography manager 510, the example ad ratio data store 512, theexample publisher data store 514, the example geography data store 516and/or, more generally, the example probe manager 414 of FIGS. 4 and 5may be implemented by hardware, software, firmware and/or anycombination of hardware, software and/or firmware. Thus, for example,any of the example baseline engine 502, the example skew engine 504, theexample probe interface 506, the example publisher manager 508, theexample geography manager 510, the example ad ratio data store 512, theexample publisher data store 514, the example geography data store 516and/or, more generally, the example probe manager 414 of FIGS. 4 and 5could be implemented by one or more analog or digital circuit(s), logiccircuits, programmable processor(s), application specific integratedcircuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)) and/or fieldprogrammable logic device(s) (FPLD(s)). When reading any of theapparatus or system claims of this patent to cover a purely softwareand/or firmware implementation, at least one of the example baselineengine 502, the example skew engine 504, the example probe interface506, the example publisher manager 508, the example geography manager510, the example ad ratio data store 512, the example publisher datastore 514, the example geography data store 516 and/or, more generally,the example probe manager 414 of FIGS. 4 and 5 is/are hereby expresslydefined to include a tangible computer readable storage device orstorage disk such as a memory, a digital versatile disk (DVD), a compactdisk (CD), a Blu-ray disk, etc. storing the software and/or firmware.Further still, the example probe manager 414 of FIGS. 4 and 5 mayinclude one or more elements, processes and/or devices in addition to,or instead of, those illustrated in FIG. 5 , and/or may include morethan one of any or all of the illustrated elements, processes anddevices.

Flowcharts representative of example machine readable instructions forimplementing the probe manager 414 of FIGS. 4 and 5 are shown in FIGS.6-7 . In these examples, the machine readable instructions compriseprograms for execution by a processor such as the processor 812 shown inthe example processor platform 800 discussed below in connection withFIG. 8 . The programs may be embodied in software stored on a tangiblecomputer readable storage medium such as a CD-ROM, a floppy disk, a harddrive, a digital versatile disk (DVD), a Blu-ray disk, or a memoryassociated with the processor 812, but the entire programs and/or partsthereof could alternatively be executed by a device other than theprocessor 812 and/or embodied in firmware or dedicated hardware.Further, although the example programs are described with reference tothe flowcharts illustrated in FIGS. 6-7 , many other methods ofimplementing the example probe manager 414 may alternatively be used.For example, the order of execution of the blocks may be changed, and/orsome of the blocks described may be changed, eliminated, or combined.

As mentioned above, the example processes of FIGS. 6-7 may beimplemented using coded instructions (e.g., computer and/or machinereadable instructions) stored on a tangible computer readable storagemedium such as a hard disk drive, a flash memory, a read-only memory(ROM), a compact disk (CD), a digital versatile disk (DVD), a cache, arandom-access memory (RAM) and/or any other storage device or storagedisk in which information is stored for any duration (e.g., for extendedtime periods, permanently, for brief instances, for temporarilybuffering, and/or for caching of the information). As used herein, theterm tangible computer readable storage medium is expressly defined toinclude any type of computer readable storage device and/or storage diskand to exclude propagating signals and to exclude transmission media. Asused herein, “tangible computer readable storage medium” and “tangiblemachine readable storage medium” are used interchangeably. Additionallyor alternatively, the example processes of FIGS. 6-7 may be implementedusing coded instructions (e.g., computer and/or machine readableinstructions) stored on a non-transitory computer and/or machinereadable medium such as a hard disk drive, a flash memory, a read-onlymemory, a compact disk, a digital versatile disk, a cache, arandom-access memory and/or any other storage device or storage disk inwhich information is stored for any duration (e.g., for extended timeperiods, permanently, for brief instances, for temporarily buffering,and/or for caching of the information). As used herein, the termnon-transitory computer readable medium is expressly defined to includeany type of computer readable storage device and/or storage disk and toexclude propagating signals and to exclude transmission media. As usedherein, when the phrase “at least” is used as the transition term in apreamble of a claim, it is open-ended in the same manner as the term“comprising” is open ended.

The program 600 of FIG. 6 begins at block 602 where the example baselineengine 502 determines whether baseline advertising information for eachInternet publisher of interest has been established. As described abovein connection with FIG. 1 , example baseline advertising information mayinclude baseline ad ratios 106, 114 for each advertiser that consumes adspace from any number of Internet publishers of interest. If no baselineadvertising information has been established (block 602), the exampleprobe interface 506 initiates probes to establish and/or otherwiseacquire baseline information among all geographies of interest for eachpublisher of interest (block 604). In some examples, the probe interface506 performs an initial probing effort in all geographies of interestwith an initial probing frequency designed to capture a thoroughbaseline ad ratio for every advertiser of interest. In other words, theinitial probing effort probing frequency may be a relatively expensiveeffort by the market researcher because a relatively greater number ofper-probe fees may be incurred if a third party probe service isemployed. Ad ratio values returned from the example initial probingeffort reflect a percentage amount of advertising presence for aparticular advertiser with the Internet publisher of interest for allgeographies of interest. As described in further detail below, theexample skew engine 504 determines a skew metric for each publisher ofinterest within each geography of interest to establish ad ratiodeviation values (block 606).

FIG. 7 illustrates an example implementation of a process fordetermining skew (block 606) of FIG. 6 . In the illustrated example ofFIG. 7 , the publisher manager 508 selects an Internet publisher ofinterest (block 702). In some examples, the publisher manager 508queries the example publisher data store 514 to identify a list ofInternet publishers of interest that are to be evaluated for theirrespective ad space activity. The example geography manager 510 selectsa geography of interest (block 704), which may be selected from a listof any number of geographies of interest stored in the example geographydata store 516. Using the selected Internet publisher of interest andthe selected geography of interest, the example skew engine 504calculates a difference between the baseline ad ratio (e.g., see FIG. 1) and the localized ad ratio value (block 706). This difference isreferred to as the ad ratio deviation, and is stored in the example adratio data store 512.

In the event the example geography manager 510 identifies anothergeography of interest (e.g., via a query to the example geography datastore 516) (block 708), control returns to block 704 to select the nextgeography of interest for the currently selected Internet publisher ofinterest. On the other hand, if all geographies of interest for theselected Internet publisher of interest have performed respective adratio deviation calculations (block 706), then the example publishermanager 508 determines whether one or more additional Internetpublishers of interest are to be evaluated (block 710). If so, controlreturns to block 702 to select the next Internet publisher of interest.

In some examples, a nominal value of skew is referred to as a generalskew that is indicative of an overall amount of variation of advertisingacross all geographies of interest, while one or more geographies thatdeviate from a baseline skew value is referred to as a special skew.Returning to FIG. 6 , the example probe interface 506 compares thecalculated ad ratio deviation values to one or more threshold values toestablish a probing frequency for each geography of interest (block608). In some examples, the probing frequency for a particular geographyof interest will be established, calculated and/or otherwise configuredto a value less than the frequency employed during the initial probingeffort, thereby saving the market researcher costs associated withprobing frequency. However, in some examples, the target probingfrequency for a particular geography of interest will be established toa value equal to or greater than the frequency employed during theinitial probing effort when values of ad ratio deviation are determinedto be relatively high and/or exceed/satisfy one or more thresholdvalues. Such threshold values may indicate and/or otherwise suggest thata relatively high amount of different advertising activity is occurringin the ad space of the Internet publisher of interest, therebyjustifying the relatively higher rates of probing frequency. Asdescribed above, while a geography of interest may exhibit a particularad ratio deviation at a first time to justify a particular probingfrequency, one or more factors may cause that geography of interest toexhibit a change in the ad ratio deviation value(s). For example, aparticular advertiser may identify that a particular geography ofinterest should receive a barrage of advertisements related to a newproduct to be released, a new movie to be released, a politicalcandidate advertisement for a localized and/or national election, or anyother change in advertising behavior.

The example skew engine 504 may determine whether to repeat a skewcalculation to identify one or more instances of special skew on aperiodic, aperiodic, scheduled and/or manual basis (block 610). If so,the example skew engine 504 is again invoked to determine skew valuesfor each geography of interest (block 606), and compares the newlycalculated ad ratio deviation values to threshold values to determinewhether one or more conditions of special skew is present (block 612).In some examples, the skew engine 504 compares the newly calculated adratio deviation values to previously calculated ad ratio deviationvalues to identify localized changes in advertising behavior.

If the difference between the newly calculated ad ratio deviation valuesfor one or more geographies of interest does not satisfy (e.g., exceed)one or more threshold values (block 614), then control returns to block610 to await another opportunity to check for instances of special skew.On the other hand, if the difference between the newly calculated adratio deviation values for one or more geographies of interest satisfies(e.g., exceeds by a threshold amount, falls short by a threshold amount)one or more threshold values (block 614), then the skew engine 504categorizes the particular Internet publisher and correspondinggeography of interest as exhibiting special skew (block 616). Based onwhich threshold(s) are satisfied, the example probe interface 506updates a probing frequency for the geograph(ies) of interest (block618).

FIG. 8 is a block diagram of an example processor platform 800structured to execute the instructions of FIGS. 6-7 to implement theprobe manager 414 of FIGS. 4 and/or 5 . The processor platform 800 canbe, for example, a server, a personal computer, a mobile device (e.g., acell phone, a smart phone, a tablet such as an iPad™), or any other typeof computing device.

The processor platform 800 of the illustrated example includes aprocessor 812. The processor 812 of the illustrated example is hardware.For example, the processor 812 can be implemented by one or moreintegrated circuits, logic circuits, microprocessors or controllers fromany desired family or manufacturer. Additionally, the example processor812 may include the example probe manager 414, which includes theexample baseline engine 502, the example skew engine 504, the exampleprobe interface 506, the example publisher manager 508, the examplegeography manager 510, the example ad ratio data store 512, the examplepublisher data store 514, and/or the example geography data store 516.

The processor 812 of the illustrated example includes a local memory 813(e.g., a cache). The processor 812 of the illustrated example is incommunication with a main memory including a volatile memory 814 and anon-volatile memory 816 via a bus 818. The volatile memory 814 may beimplemented by Synchronous Dynamic Random Access Memory (SDRAM), DynamicRandom Access Memory (DRAM), RAMBUS Dynamic Random Access Memory (RDRAM)and/or any other type of random access memory device. The non-volatilememory 816 may be implemented by flash memory and/or any other desiredtype of memory device. Access to the main memory 814, 816 is controlledby a memory controller.

The processor platform 800 of the illustrated example also includes aninterface circuit 820. The interface circuit 820 may be implemented byany type of interface standard, such as an Ethernet interface, auniversal serial bus (USB), and/or a PCI express interface.

In the illustrated example, one or more input devices 822 are connectedto the interface circuit 820. The input device(s) 822 permit(s) a userto enter data and commands into the processor 812. The input device(s)can be implemented by, for example, a microphone, a keyboard, a button,a mouse, a touchscreen, a track-pad, a trackball, isopoint and/or avoice recognition system.

One or more output devices 824 are also connected to the interfacecircuit 820 of the illustrated example. The output devices 824 can beimplemented, for example, by display devices (e.g., a light emittingdiode (LED), an organic light emitting diode (OLED), a liquid crystaldisplay, a cathode ray tube display (CRT), a touchscreen, a printerand/or speakers). The interface circuit 820 of the illustrated example,thus, typically includes a graphics driver card, a graphics driver chipor a graphics driver processor.

The interface circuit 820 of the illustrated example also includes acommunication device such as a transmitter, a receiver, a transceiver, amodem and/or network interface card to facilitate exchange of data withexternal machines (e.g., computing devices of any kind) via a network826 (e.g., an Ethernet connection, a digital subscriber line (DSL), atelephone line, coaxial cable, a cellular telephone system, etc.).

The processor platform 800 of the illustrated example also includes oneor more mass storage devices 828 for storing software and/or data.Examples of such mass storage devices 828 include floppy disk drives,hard drive disks, compact disk drives, Blu-ray disk drives, RAIDsystems, and digital versatile disk (DVD) drives.

The coded instructions 832 of FIGS. 5-6 may be stored in the massstorage device 828, in the volatile memory 814, in the non-volatilememory 816, and/or on a removable tangible computer readable storagemedium such as a CD or DVD.

From the foregoing, it will be appreciated that example methods,systems, apparatus and/or articles of manufacture to identify publisheradvertising behavior have been disclosed to achieve improved serverefficiency when gathering information regarding which advertisers areconsuming and/or otherwise purchasing ad space from the Internetpublishers of interest. In particular, disclosed examples reduce probingby computer networking equipment within one or more networks, includingthe Internet, by establishing probing rates for the probing equipment ina manner that is proportional to the amount of advertising diversitydetected within each geography of interest for each particular Internetpublisher of interest. This approach reduces probing and/or reducesunnecessary network traffic. Further, examples disclosed herein savesprocessor resources by reducing the number of probing events, andreduces memory usage by avoiding unnecessary collection and/or storageof data which is unneeded to show an interesting change in behavior. Instill other examples disclosed herein, this approach increases probingefforts when one or more geographies of interest are underrepresentedand/or otherwise in need of greater sample frequencies to derivestatistically significant results of market behavior.

Although certain example methods, apparatus and articles of manufacturehave been disclosed herein, the scope of coverage of this patent is notlimited thereto. On the contrary, this patent covers all methods,apparatus and articles of manufacture fairly falling within the scope ofthe claims of this patent.

What is claimed is:
 1. An apparatus to probe an Internet publisher, theapparatus comprising: a skew engine to determine a first advertisingdeviation of the Internet publisher based on a difference between abaseline advertising ratio and a local advertising ratio associated witha geography; a probe interface to configure a first probing frequency ata network-connected server based on a comparison of the firstadvertising deviation to a first threshold, the network-connected serverassociated with the geography, the first probing frequency correspondingto probing efforts for the geography of the Internet publisher; and aprobe manager to re-configure the first probing frequency at thenetwork-connected server by modifying the first probing frequency to asecond probing frequency to manage the probing efforts for the geographyin response to a difference between the first advertising deviation anda second advertising deviation of the Internet publisher satisfying asecond threshold, the probe interface to transmit an instruction to thenetwork-connected server to cause the network-connected server toperform the probing efforts at the second probing frequency.
 2. Theapparatus of claim 1, wherein the probe manager is to: re-configure thefirst probing frequency by decreasing the first probing frequency to thesecond probing frequency to reduce computational probing waste inresponse to determining an advertising diversity decreased.
 3. Theapparatus of claim 1, wherein the baseline advertising ratio reflects aquantity of advertising space consumed on a website of the Internetpublisher, the quantity of advertising space independent of thegeography.
 4. The apparatus of claim 1, wherein the geography is a firstgeography and further including a second geography, wherein the probeinterface is to: obtain data from a first server associated with thefirst geography; and obtain data from a second server associated withthe second geography, the probe interface to obtain data from the firstand second servers via a network.
 5. The apparatus of claim 4, whereinthe probe interface is to cause at least one of the first server or thesecond server to navigate to a website of the Internet publisher.
 6. Theapparatus of claim 1, wherein the probe manager is to modify the firstprobing frequency to the second probing frequency in response todetermining an advertising diversity increased.
 7. The apparatus ofclaim 1, wherein the probe manager is to increase the first probingfrequency to the second probing frequency based on a ratio of the firstadvertising deviation and the second advertising deviation.
 8. Atangible machine readable storage medium comprising machine accessibleinstructions that, when executed, cause a machine to, at least:determine a first advertising deviation of an Internet publisher basedon a difference between a baseline advertising ratio and a localadvertising ratio associated with a geography; configure a first probingfrequency at a network-connected server based on a comparison of thefirst advertising deviation to a first threshold, the network-connectedserver associated with the geography, the first probing frequencycorresponding to a plurality of probing efforts for the geography of theInternet publisher; re-configure the first probing frequency at thenetwork-connected server by modifying the first probing frequency to asecond probing frequency to manage the plurality of probing efforts forthe geography in response to a difference between the first advertisingdeviation and a second advertising deviation of the Internet publishersatisfying a second threshold; and transmit an instruction to thenetwork-connected server to cause the network-connected server toperform the probing efforts at the second probing frequency.
 9. Thetangible machine readable storage medium of claim 8, wherein theinstructions, when executed, cause the machine to: re-configure thefirst probing frequency by decreasing the first probing frequency to thesecond probing frequency to reduce computational probing waste inresponse to determining an advertising diversity decreased.
 10. Thetangible machine readable storage medium of claim 8, wherein thebaseline advertising ratio reflects a quantity of advertising spaceconsumed on a website of the Internet publisher, the quantity ofadvertising space independent of the geography.
 11. The tangible machinereadable storage medium of claim 8, wherein the geography is a firstgeography and further including a second geography, wherein theinstructions, when executed, case the machine to: obtain data from afirst server associated with the first geography; and obtain data from asecond server associated with the second geography, the machine toobtain data from the first and second servers via a network.
 12. Thetangible machine readable storage medium of claim 11, wherein theinstructions, when executed, cause the machine to initiate instructionsto cause at least one of the first server or the second server tonavigate to a website of the Internet publisher.
 13. The tangiblemachine readable storage medium of claim 8, wherein the instructions,when executed, cause the machine to modify the first probing frequencyto the second probing frequency in response to determining anadvertising diversity increased.
 14. The tangible machine readablestorage medium of claim 8, wherein the instructions, when executed,cause the machine to increase the first probing frequency to the secondprobing frequency based on a ratio of the first advertising deviationand the second advertising deviation.
 15. A system to probe an Internetpublisher, the system comprising: means for determining a firstadvertising deviation of the Internet publisher based on a differencebetween a baseline advertising ratio and a local advertising ratioassociated with a geography; means for configuring a first probingfrequency at a network-connected server based on a comparison of thefirst advertising deviation to a first threshold, the network-connectedserver associated with the geography, the first probing frequencycorresponding to probing efforts for the geography of the Internetpublisher; and means for re-configuring the first probing frequency atthe network-connected server by modifying the first probing frequency toa second probing frequency to manage the probing efforts for thegeography in response to a difference between the first advertisingdeviation and a second advertising deviation of the Internet publishersatisfying a second threshold, the configuring means to transmit aninstruction to the network-connected server to cause thenetwork-connected server to perform the probing efforts at the secondprobing frequency.
 16. The system of claim 15 wherein the re-configuringmeans is to: re-configure the first probing frequency by decreasing thefirst probing frequency to the second probing frequency to reducecomputational probing waste in response to determining an advertisingdiversity decreased.
 17. The system of claim 15, wherein the baselineadvertising ratio reflects a quantity of advertising space consumed on awebsite of the Internet publisher, the quantity of advertising spaceindependent of the geography.
 18. The system of claim 15, wherein thegeography is a first geography and further including a second geography,wherein the configuring means is to: obtain data from a first serverassociated with the first geography; and obtain data from a secondserver associated with the second geography, the configuring means toobtain data from the first and second servers via a network.
 19. Thesystem of claim 18, wherein the configuring means is to cause at leastone of the first server or the second server to navigate to a website ofthe Internet publisher.
 20. The system of claim 15, wherein there-configuring means is to modify the first probing frequency to thesecond probing frequency in response to determining an advertisingdiversity increased.
 21. The system of claim 15, wherein there-configuring means is to increase the first probing frequency to thesecond probing frequency based on a ratio of the first advertisingdeviation and the second advertising deviation.
 22. An apparatuscomprising: memory; machine readable instructions; and at least oneprocessor to execute the machine readable instructions to: determine afirst advertising deviation of an Internet publisher based on adifference between a baseline advertising ratio and a local advertisingratio associated with a geography; configure a first probing frequencyat a network-connected server based on a comparison of the firstadvertising deviation to a first threshold, the network-connected serverassociated with the geography, the first probing frequency correspondingto probing efforts for the geography of the Internet publisher;re-configure the first probing frequency at the network-connected serverby modifying the first probing frequency to a second probing frequencyto manage the probing efforts for the geography in response to adifference between the first advertising deviation and a secondadvertising deviation of the Internet publisher satisfying a secondthreshold; and transmit an instruction to the network-connected serverto cause the network-connected server to perform the probing efforts atthe second probing frequency.
 23. The apparatus of claim 22, wherein theat least one processor is to execute the instructions to: re-configurethe first probing frequency by decreasing the first probing frequency tothe second probing frequency to reduce computational probing waste inresponse to determining an advertising diversity decreased.
 24. Theapparatus of claim 22, wherein the baseline advertising ratio reflects aquantity of advertising space consumed on a website of the Internetpublisher, the quantity of advertising space independent of thegeography.
 25. The apparatus of claim 22, wherein the geography is afirst geography and further including a second geography, wherein the atleast one processor is to execute the instructions to: obtain data froma first server associated with the first geography via a network; andobtain data from a second server associated with the second geographyvia the network.
 26. The apparatus of claim 25, wherein the at least oneprocessor is to execute the instructions to cause at least one of thefirst server or the second server to navigate to a website of theInternet publisher.
 27. The apparatus of claim 22, wherein the at leastone processor is to execute the instructions to modify the first probingfrequency to the second probing frequency in response to determining anadvertising diversity increased.
 28. The apparatus of claim 22, whereinthe at least one processor is to execute the instructions to increasethe first probing frequency to the second probing frequency based on aratio of the first advertising deviation and the second advertisingdeviation.